How to Use the PractiTest MCP in CrewAI

Deploy autonomous QA crews using CrewAI to research requirements and execute test runs in PractiTest without human oversight.

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MCP Servers — Included with Plan

Connect PractiTest MCP to CrewAI

Create your Vinkius account to connect PractiTest to CrewAI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup PractiTest with CrewAI

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Specialized agent collaboration

Assign one agent to `list_requirements` while another handles `create_run` execution. CrewAI manages the collaboration, ensuring the research agent passes the right IDs to the executor. This keeps your QA operations focused. One agent acts as the monitor, checking the status of previous runs before the next batch starts.

Autonomous test suite maintenance

Your crew can proactively use `list_tests` to identify outdated cases and `create_test` to add new coverage. The agents work independently to keep your project updated. By setting clear roles, you avoid overlapping work. The agents share memory of the project state, allowing them to make informed decisions about what to run next.

Automated regression execution

The crew executes `create_instance` and `create_run` as part of an autonomous pipeline. You define the goal, and the agents handle the tool calls required to reach it. This setup is perfect for high-velocity environments. Your team defines the strategy, and the crew performs the repetitive work of logging and verifying results.

Setup guide

Set up PractiTest MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke PractiTest tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="PractiTest Analyst",
    goal="Access and analyze PractiTest data via MCP.",
    backstory="Expert analyst with direct PractiTest access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent PractiTest transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="PractiTest Analyst",
        goal="Access and analyze PractiTest data via MCP.",
        backstory="Expert analyst with direct PractiTest access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent PractiTest transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

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Common questions about PractiTest MCP in CrewAI

Yes. By adding the server to your agents, you can build a crew that interacts with your projects to query data and record execution results autonomously.

Agents use shared memory to pass tool results between them. If one agent finds a test ID, the others can use it immediately for the next step in the sequence.

You can apply a tool filter to your agents. This restricts them to specific actions, ensuring they only perform the tasks you have explicitly authorized.

The agents can perform sequential or hierarchical execution. This allows them to manage large volumes of test runs without overwhelming the API rate limits.

Your project data is processed through secure, ephemeral sessions. The MCP Server ensures that only the authorized agents can access your requirements and test logs.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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